It is virtually impossible for a business user to know or determine the database tables and archiving objects that are associated or linked to any particular business process. Consequently, a systems person must perform a technical analysis of a database to determine the database tables that are voluminous, and then implement an archiving strategy based on this information. Unfortunately, this procedure and strategy usually do not identify business critical processes because of the lack of functions in business systems that can extract information showing the relationship of database tables, archiving objects, and business processes. Simply put, current archiving strategies are purely database size and/or growth driven as a result of technical monitoring of such databases.
Similarly, controlling a system landscape in terms of data volume management (DVM) measures such as avoidance, summarization, deletion, or archiving of data is one of the most complex tasks and projects in the whole lifecycle of heterogenous system landscapes. The reason for the complexity is the unique fingerprint of each and every system in a customer's environment. Every system is unique in terms of configuration and customizing, and this uniqueness results in differences of how much and to which tables data are written. As a consequence, customers are burdened with the task of identifying data objects (e.g., database tables) that should be focused on in a data volume management concept, rather than focusing on the evaluation of residence times or the selection of type of documents that should be deleted or should be archived.
For example, in an average landscape there is normally an enterprise resource planning (ERP) system, a business information warehouse (BW) system, a customer relations management (CRM) system, and an exchange infrastructure (XI)/process integration (PI). With just these four products in a landscape, the system may have up to a hundred thousand or more database tables in the landscape. Due to historical reasons, customers are starting to analyze their system landscapes from a database table level. While this may have been doable years ago, nowadays it is nearly impossible to follow this kind of approach without having some criteria on how to set the priority correspondingly.